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Getting Started with Natural Language Processing (NLP)

by Dhiren Gala

NLP helps build systems that can automatically analyze, process, summarize and extract meaning from natural language text. In a nutshell, NLP helps machines mimic human behaviour and allows us to build applications that can reason about different types of documents. NLP open-source libraries are tools that allow you to build your own NLP applications. These libraries can be used to develop many different types of applications, like Speech Recognition, chatbots, Sentimental Analysis, Email Spam Filtering, Language Translator, search engines, and question answering systems. NLTK is one of the most popular NLP libraries in Python. It provides easy-to-use interfaces to corpora and lexical resources such as WordNet, along with statistical models for common tasks such as part-of-speech tagging and noun phrase extraction. Following list has libraries for most basic Sentimental Analysis VADER (Valence Aware Dictionary and sEntiment Reasoner) Tool, collection of NLP resources – blogs, books, tutorials, and more. Check out the list of free, open source libraries to help you with your projects:

Some Popular Open Source Libraries to get you started

Utilize the below libraries to tokenize, implement part-of-speech tagging, stemming, sentiment analysis, topic segmentation, and named entity recognition.

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